5G and Beyond: The Future of IoT
- Length: 256 pages
- Edition: 1
- Language: English
- Publisher: Chapman and Hall/CRC
- Publication Date: 2022-02-04
- ISBN-10: 0367493292
- ISBN-13: 9780367493295
- Sales Rank: #0 (See Top 100 Books)
The Internet of Things (IoT) has seen the eventual shift to the Internet of Everything in the recent years, unveiling its ubiquitous presence spanning from smart transports to smart healthcare, from smart education to smart shopping. With the 5G rollouts across the different countries of the world, it raises newer perspectives toward the integration of 5G in IoT. For IoT-based smart devices, 5G not only means speed, but also better stability, efficiency, and more secure connectivity. The reach of 5G in IoT is extending in multifarious areas like self-driving vehicles, smart grids for renewable energy, AI-enabled robots on factory floors, intelligent healthcare services . . . The endless list is the real future of 5G in IoT.
Features:
- Fundamental and applied perspectives to 5G integration in IoT
- Transdisciplinary vision with aspects of Artificial Intelligence, Industry 4.0, and hands-on practice tools
- Discussion of trending research issues in 5G and IoT As 5G technologies catalyze a paradigm shift in the domain of IoT, this book serves as a reference for the researchers in the field of IoT and 5G, proffering the landscape to the trending aspects as well as the key topics of discussion in the years to come.
Cover Half Title Title Page Copyright Page Table of Contents Preface Editors Contributors Part I: Fundamental Architectural Concepts for 5G and IoT Chapter 1: The Impact of Artificial Intelligence on 5G-Enabled IoT Networks 1.1 Introduction 1.1.1 Artificial Intelligence: State of the Art and Prospects 1.1.2 Important Subsets of AI 1.1.3 Background of AI 1.1.4 Current Research in 5G 1.2 Role of AI and 5G in Digital Transformation Across Industries 1.3 Impact of Machine Learning for a 5G Future 1.3.1 Categorization of Machine Learning Models for 5G Deployment 1.4 Potential and Limitations of AI and Machine Learning for 5G 1.4.1 Potential of AI 1.4.2 Limitations of Using AI and ML 1.5 Requirements and Key Enabling Technology in 5G IoT 1.6 Artificial Intelligence Driven Cases for Real-Time Business and 5G IoT 1.6.1 COVID-19, Digital Healthcare and the Role of 5G 1.6.2 Real-World Business Use Cases for AI 1.7 Conclusions References Chapter 2: Attacks, Security Concerns, Solutions, and Market Trends for IoT 2.1 Introduction 2.1.1 Layered Architecture of IoT Network 2.1.2 Building Blocks of IoT System 2.2 IoT Devices 2.2.1 IoT Device Lifecycle 2.2.2 Benefits of IoT Devices 2.2.3 Drawbacks of IoT Devices 2.3 IoT Network Technologies 2.4 Data Aggregation in IoT 2.5 Attacks and Security Threats in IoT 2.5.1 Attacks on Different Network Layers 2.5.2 Attacking Tools Used in IoT 2.5.3 Solutions to IoT Security Attacks 2.5.3.1 Traditional Defense Techniques 2.5.3.2 Current Defense Techniques 2.6 Optimization of IoT Network 2.6.1 WOA Algorithm 2.6.2 Simulated Annealing 2.7 Challenges in IoT 2.8 IoT Market Analysis References Chapter 3: Intelligence and Security in the 5G-Oriented IoT 3.1 Introduction 3.1.1 5G Integration with IoT 3.2 Detailed Components of IoT–5G Integration 3.2.1 Layered Architecture 3.3 Properties 3.3.1 Quality of Service 3.3.2 Functional Requirements 3.3.3 Non-Functional Requirements 3.4 Security 3.4.1 Recognition Layer 3.4.2 Connectivity Layer 3.4.3 Support Layer 3.4.4 Application Layer 3.4.5 Business Layer 3.5 Intelligence in the 5G-Oriented Internet of Things 3.6 Tools 3.6.1 Hadoop 3.6.2 Spark 3.6.3 Hive 3.6.4 R Studio 3.6.5 Python 3.6.6 CupCarbon 3.7 Open Issues and Future Research Directions 3.8 Conclusion References Chapter 4: Advances in Mobile Communications from a 5G Perspective 4.1 Introduction 4.2 Cognitive Radio Perspectives 4.2.1 CR Functionalities 4.2.1.1 Spectrum Sensing 4.2.1.2 Spectrum Management 4.2.1.3 Spectrum Sharing 4.2.1.4 Spectrum Mobility 4.2.2 Cognitive Radio in 5G 4.2.2.1 Antennas for CR in 5G 4.2.2.2 Cognitive Engines 4.2.2.3 Improved PHY Technologies 4.3 Small-Cell Coverage in 5G Communications 4.3.1 Trends in Small Cells 4.3.2 Technical Aspects of Small Cells 4.3.2.1 Carrier Aggregation 4.3.2.2 Multi-Cell Cooperation 4.3.2.3 Massive MIMO 4.3.2.4 Multiple Access Techniques 4.4 Small Cells and 5G 4.5 IoT Perspective 4.6 Directing CRNs toward IoT 4.7 How CRNs Fulfill IoT Requirements 4.7.1 Channel Allocation 4.7.2 Protocol Design 4.7.3 Energy Harvesting 4.8 Small Cells Fulfilling the IoT Requirement 4.9 Small-Cell Deployment through CR 4.10 Conclusions References Chapter 5: The Role of IoT in Smart Technologies 5.1 Introduction 5.1.1 Components of the Smart Home 5.2 Communication Protocols and their Features 5.2.1 Desirable Attributes for IoT Communication Protocols 5.3 Basics of Prime IoT Communication Protocols 5.3.1 Bluetooth [6] 5.3.2 Bluetooth Low Energy [7] 5.3.3 ZigBee [8] 5.3.4 Z-Wave [9] 5.3.5 IPv6LowPAN [10] 5.3.6 Thread [11] 5.3.7 WiFi (Wireless Fidelity) [12] 5.3.8 Cellular [13] 5.3.9 Near Field Communication (NFC) [14] 5.3.10 Sigfox [15] 5.3.11 LoRaWAN [16] 5.4 Risks with Wireless Protocols in the Context of IoT 5.5 Conclusion References Part II: Applied Scenarios of 5G and IoT Chapter 6: Realization of New Radio 5G-IoT Connectivity Using mmWave-Massive MIMO Technology 6.1 Introduction 6.2 Waveform Design Approaches 6.2.1 OFDM 6.2.2 FBMC 6.2.3 GFDM 6.2.4 UFMC 6.3 Spatial Multiplexing 6.4 Precoding 6.4.1 Digital Precoding 6.4.1.1 SU Digital Precoding 6.4.1.2 MU Digital Precoding 6.4.2 Analog Beamforming 6.4.2.1 Beam Steering 6.4.2.2 Beam Training 6.4.3 Hybrid Precoding 6.4.3.1 SU Hybrid Precoding 6.4.3.2 MU Hybrid Precoding 6.4.3.2.1 Two-Stage Hybrid Precoding 6.5 Channel Measurement and Modeling 6.5.1 Channel Measurement 6.5.2 Channel Modeling 6.6 Channel Estimation 6.7 Training-Based Channel Estimation 6.7.1 Blind Channel Estimation 6.7.2 Compressive Sensing-Based CE Scheme 6.8 Conclusions Abbreviations References Chapter 7: Algebraically Constructed Short Sequence Families for 5G NOMA Techniques 7.1 Introduction 7.2 Non-Orthogonal Multiple Access (NOMA) System 7.2.1 Sparse Code Multiple Access (SCMA) 7.2.2 Pattern Division Multiple Access (PDMA) 7.2.3 Multiple-User Shared Access (MUSA) 7.3 Sequence Construction: Modify Frequency Hop Codes and Lagrange Sequences for MUSA and PDMA Systems 7.3.1 Sidelnikov, Legendre, and Complex Legendre Sequence Definition 7.3.2 Generalized Welch (GW) Shifting Sequence Construction 7.3.3 Construction of Short Patterns for PDMA and MUSA 7.4 Performance Comparison of Different PDMA Patterns 7.5 Conclusion Acknowledgment References Chapter 8: Ambient Backscatter Communication: A Solution for Energy-Efficient 5G-Enabled IoT 8.1 Introduction 8.1.1 Types of BackCom Systems 8.1.2 Monostatic BackCom System (MBCS) 8.1.2.1 Bistatic BackCom System (BBCS) 8.1.2.2 Ambient BackCom System (ABCS) 8.1.3 Overview of BackCom Systems 8.1.4 Backscatter Transmitter 8.1.5 Backscatter Receiver 8.2 Broad Areas of BackCom Research 8.2.1 Signal Processing 8.2.1.1 Channel Coding 8.2.1.2 Interference 8.2.1.3 Channel Decoding 8.2.1.4 Signal Detection 8.2.2 BackCom: Wireless Communications 8.2.2.1 Modulation 8.2.2.2 Multiple Access Techniques in BackCom Systems 8.2.3 BackCom: Wireless Information and Power Transfer 8.2.4 Task Scheduling and Resource Allocation 8.3 Mathematical Aspects of ABCS 8.4 Upcoming Backscatter Communication Techniques 8.4.1 Visible Light BackCom Systems (VLBCS) 8.4.2 Relay-Assisted BackCom System 8.4.3 mm-wave-Based BackCom 8.4.4 Long Range (Lo-Ra) BackCom 8.4.5 Ultra-Wide Band (UWB) BackCom 8.4.6 Full-Duplex BackCom 8.4.7 Cognitive Radio Network (CRN) with BackCom 8.4.8 Non-Orthogonal Multiple Access (NOMA) in BackCom 8.5 Applications of BackCom 8.5.1 BackCom in Medical Science 8.5.2 BackCom for Smart Cities/Smart Homes 8.5.3 BackCom in Smart Factories 8.5.4 BackCom in Precision Agriculture 8.6 Open Research Issues 8.6.1 Interference Management 8.6.2 Physical Layer Security 8.6.3 Machine-Learning Algorithms 8.6.4 Achieving High Data Rates 8.7 Conclusion References Chapter 9: Deployment and Analysis of Random Walk and Random Waypoint Mobility Model for WSN-Assisted IoT Hierarchical Framework 9.1 Introduction 9.2 Related Work 9.3 System Model 9.3.1 Proposed Framework 9.3.2 Communication Constraints 9.3.2.1 Communication Constraints for Local Cluster 9.3.2.2 Communication Constraints across Clusters 9.3.3 Different Network Scenarios 9.3.4 Assumptions 9.3.5 Energy Model 9.3.6 Network Lifetime 9.4 Energy-Efficient Routing 9.5 Result Analysis and Discussion 9.6 Conclusion References Chapter 10: Multi-User Detection in Uplink Grant-Free NOMA with Dynamic Random Access Using Sinusoidal Sequences 10.1 Introduction 10.1.1 Background and Motivation 10.1.2 Related Works 10.1.3 Contribution 10.1.4 Notation 10.2 System Model 10.3 System Model with Sinusoidal Sequences 10.3.1 Signal Model for Sinusoidal Spreading Sequences 10.3.2 Sparse Signal Representation with Sinusoidal Sequence 10.4 SPICE-based AUD 10.4.1 Finding Active User Indices Using SPICE 10.4.2 Fast Computation of R using FFT 10.5 Subspace Estimation-Based Fast AUD 10.5.1 Estimating the Number of Active UEs 10.5.2 Estimating the Active UE Indices 10.6 User Activity Detection over RA Opportunity 10.6.1 Statistics Sufficient for User Activity Detection 10.6.2 Refining the Active User Set 10.7 Channel Estimation with Dynamic RA 10.7.1 Channel Estimation 10.7.2 Data Detection 10.7.3 Reliable Recovery of Transmitted Data Symbols 10.7.4 Summary of Proposed AUD, CE, and DD 10.7.5 Scope of Performance Improvement with Prior Noise and Channel Statistics 10.8 Numerical Analysis 10.8.1 Simulation Setup 10.8.2 Simulation Results 10.9 Conclusions Proof of Lemma Thresholds for SPICE References Chapter 11: 5G-Enabled IoT: Applications and Case Studies 11.1 Introduction 11.2 Emerging IoT Applications 11.2.1 Smart Healthcare System 11.2.1.1 Sensor Node Architecture 11.2.1.2 IoT-Based 5G-CCN Architecture 11.2.1.3 Small-Cell Technology in 5G 11.2.1.4 5G-Based Mobile Edge Computing 11.2.2 Smart Agriculture 11.2.2.1 Image Electronic Fence 11.2.2.2 IoT-Based Smart Fish Agriculture 11.2.2.3 AREThOU5A Project 11.2.3 Smart City 11.2.3.1 Smart Camera 11.2.3.2 Smart Grid 11.2.3.3 Intelligent Transportation System 11.2.3.4 Smart Malls 11.2.3.5 Smart Surveillance System 11.2.3.6 Smart Museums 11.2.4 Smart Home 11.2.4.1 Femtocell for Smart Home 11.2.4.2 Home Energy Management System 11.2.4.3 Distributed Mobility Management 11.2.5 Industrial Automation 11.2.5.1 5G-Based Network Slicing 11.2.5.2 Smart Manufacturing 11.2.5.3 Smart Mining Industry 11.2.5.4 Wireless Industrial Automation 11.3 Open Issues and Challenges 11.4 Conclusion References Chapter 12: Hands-On Practice Tools for 5G and IoT 12.1 Introduction 12.1.1 5G Mobile Communications 12.1.2 Internet of Things (IoT) Technology 12.2 Challenges and Opportunities 12.2.1 5G Challenges and Opportunities 12.2.1.1 Challenges 12.2.1.2 Opportunities 12.2.2 IoT Challenges and Opportunities 12.2.2.1 Challenges 12.2.2.2 Opportunities 12.3 Paradigms for 5G and IoT Tools 12.3.1 Adaptive IP 12.3.1.1 Basic 12.3.1.2 Installation Requirements 12.3.2 5G Automation 12.3.2.1 Basic 12.3.2.2 Installation Requirements 12.3.3 OpenBalena 12.3.3.1 Basic 12.3.3.2 Installation Requirements 12.3.3.3 Commands 12.4 Conclusions References Index
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